Curriculum and Courses

Course Descriptions

• MBAI 5100G - Business Analytics

  This course will provide coverage of concepts and tools used in different stages of a data analytics project, including problem definition, data collection and preparation, data analysis, and knowledge transfer. Statistical and other analytical tools such as data mining, machine learning, social network analytics, text mining, and their application to business will be explored.

  In the current business world, data is a crucial valuable asset owned by companies. It is vital for businesses to be able to effectively and efficiently define their problems, collect required data, examine the data, and communicate this information in an appropriate manner to decision-makers. Given the massive amount of data available and constant technological advancements in the field of data analytics, it is crucial that students gain the skills required to tackle these data-related problems. This course will provide hands-on training for learning these sought-after skills.

• MBAI 5110G - Big Data Systems Design
  The ability for organizations to ingest and analyze significant volumes of data as it is generated and retrospectively is becoming a fundamental organization need for organizational success. Big Data systems design is a design and planning approach that enables the systemic planning of how an organization will ingest and analyze these significant volumes of data for a given organization's objective(s). The goal of Big Data systems design is to improve organizational success through improved organizational processes and improved customer experiences. This course enables students to combine solution components based on the type of Big Data and organizational objective to formulate an integrated Big Data systems design. Solution components include Big Data storage, Big Data processing, and Big Data analytics including artificial intelligence. Students will also assess how the Big Data systems design can be provisioned in the cloud.
• MBAI 5200G - Ethical and Legal Issues in Analytics and AI

  This course highlights key legal and ethical issues related to data analytics and AI. Increasingly, scholars and practitioners are urging data scientists and businesspersons to be more cognizant of the accidental and intentional harms caused by the widespread deployment of machine learning and AI. This course examines potential liabilities in law related to data analytics and AI and juxtaposes legal requirements with ethical considerations. The course will also explore some of the most pressing ethical issues related to data analytics and AI. This course situates these explorations in the context of a set of core guiding principles for ethical and responsible data management.

  Possible topics include: obtaining meaningful consent to the collection of data; standard contractual provisions related to data analytics; liabilities related to outsourcing elements of data analytics (jurisdiction); privacy-related torts, negligence liability; ethical frameworks; implicit bias and the problem of bias in AI; tensions fairness and IP rights in black box AI; and the principles of ethical research in AI.

• MBAI 5300G - Programming and Data Processing
  The first part of the course studies data processing using the following Python libraries: Pandas, Matplotlib, NumPy, SciPy, and others. Jupyter notebooks will be used for visualization. In the process, the course introduces Calculus and Statistics for machine learning. The second part of the course studies natural language processing techniques, network analysis, weblog data analysis, and data integration techniques including data wrangling.
• MBAI 5310G - Artificial Intelligence Programming
  Students will learn to program a computer system to make predictions on, classify, or cluster data that the system has never seen before. Topics include theory and practice of supervised and unsupervised learning such as reinforcement learning, covering well-known algorithms such as linear regression, Naïve Bayes, support vector machines, ensemble methods, K-means, and convolutional and recurrent neural networks. The course uses the Python programming language with TensorFlow and Keras.
• MBAI 5400G - Visualization and Storytelling
  This is a highly interactive and hands-on course on data visualization and storytelling designed to help students understand important concepts and techniques used to transform complex data into powerful visuals. Students will use popular, innovative, and industry-standard data visualization tools to create powerful reports, dashboards, and coherent data stories that will help individuals and organizations make fact-based decisions. Students will apply predictive analytics tools to discover data patterns such as customer purchase behavior, sales trends, or production bottlenecks to improve business decision-making.
• MBAI 5410G - Digital Transformation
  In today’s business world, it has become increasingly important for organizations to deploy new digital technologies to survive, grow and transform. This course will provide students with a critical understanding of the systems, techniques, tools, methodologies, and platforms needed to enable enterprise transformation in the digital era. Strategic and operational issues surrounding digital transformation, including project management, leadership and change, enterprise architecture/infrastructure, business process improvement, and implementation methodologies will be considered.
• MBAI 5500G - Security, Privacy and Trust in AI Systems

  Artificial Intelligence (AI) increasingly impacts how humans live, work, and play online and in the physical world. In all of their interactions with AI and the physical world, humans produce great quantities of data that are available for AI to analyze and make inferences from. This raises natural questions about the potential for use, misuse, and protection of these data that can go beyond purely legal approaches.

  This course uses a sociotechnical outlook (humans and machines work together as a system) to examine AI and its interaction with privacy security and trust in the light of current and potential future advances. Using case studies, reflection, and theory, the course will examine technologies and techniques of location-based analytics, voice-enabled systems, personal AI-based assistants and blockchain as well as potential technologies of the (near and medium-term) future.

  The course will cover use, ethics, efficacy and impact, positive and negative, on privacy and security as well as the impacts these technologies may have on business, society and individuals as well as human-AI trust (and the perception of AI trustworthiness). The course will examine AI- and data-focused security tools and techniques as well as ways to help protect data whilst still enabling their use, including differential privacy and tools for trustworthy AI.

• MBAI 5600G - Applied Integrative Analytics Projects

  The capstone project is completed in the spring term in an intensive pass/fail course over an 8-week period.

  This course integrates the theory and skills learned in the MBAI program through an applied integrative capstone project where students work individually or in small teams over the 6 weeks to scope, design, and implement analytics or AI solution to a real-world problem.

  Students meet twice a week to work on projects and deliver on milestones to steadily progress towards a solution culminating with a report and presentation at the end of the class which demonstrates an application of skills and knowledge from the various domains in the program including technical, managerial, ethical and communications.

• MBAI 5700G - Business Analytics Internship

  The Internship option can vary in duration from 4 to 16 months depending on the nature of the position, the needs of the employer, and the student.

  The Business Analytics Internship course is an important experiential learning component of the MBAI program, and its objective is to provide students with practical exposure to actual work environments in analytics and AI, which is essential for a more complete understanding of the application of analytical and AI theories and procedures.

  The Internship program permits MBAI students to be registered who have met the minimum requirements of the program. The result of the program and course is to further develop a student’s skill set and experience in their field of study and provide them with an opportunity to gain actual work experience in organizations they may consider for future careers post-graduation.